US9031355B2 - Method of system for image stabilization through image processing, and zoom camera including image stabilization function - Google Patents
Method of system for image stabilization through image processing, and zoom camera including image stabilization function Download PDFInfo
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- US9031355B2 US9031355B2 US13/729,302 US201213729302A US9031355B2 US 9031355 B2 US9031355 B2 US 9031355B2 US 201213729302 A US201213729302 A US 201213729302A US 9031355 B2 US9031355 B2 US 9031355B2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
- G06T7/74—Determining position or orientation of objects or cameras using feature-based methods involving reference images or patches
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- G06T7/0044—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
Definitions
- Methods and apparatuses consistent with exemplary embodiments relate to image stabilization through image processing, and a zoom camera including an image stabilization function.
- An image captured by a surveillance camera displays a current state of a place where the surveillance camera is installed through a monitor in a police station or a management office of a building.
- a surveillance camera has a zoom function to enlarge or reduce an object to provide lots of user convenience.
- an optical axis error occurs when an imaging device, such as a plurality of lens groups and a charge-coupled device (CCD), is assembled in the surveillance camera or due to various factors such as a tolerance of an optical system, and thus, an optical axis of the surveillance camera is changed according to zoom change.
- an imaging device such as a plurality of lens groups and a charge-coupled device (CCD)
- CCD charge-coupled device
- FIGS. 1A to 1C are images showing when an optical axis error occurs in an image captured by a zoom camera.
- a portion marked with ‘+’ in FIG. 1A represents a central area of the image.
- the central area marked with ‘+’ of FIG. 1A is moved as shown in FIG. 1B , which shows that an optical axis error occurs.
- FIG. 1C there is a need for a method of compensating for the optical axis error so that the central area of the image is maintained at its original position even after the image is enlarged.
- One or more exemplary embodiments provide a method and system for determining whether an input image includes a representative feature portion through image processing and image stabilization by using an image matching method when the input image includes the representative feature portion and compensating for the optical axis error by using optical flow information if the input image includes no representative feature portion, and a zoom camera including an image stabilization function.
- a method of image stabilization including: determining whether an input image comprises a representative feature portion; sampling the representative feature portion to generate a sampled image if it is determined that the input image comprises the representative feature portion; enlarging the sampled image, matching the enlarged sampled image with the sampled image, and obtaining a central coordinate of the matched image; and aligning an optical axis by calculating a difference between the central coordinate of the matched image and a central coordinate of the sampled image.
- the representative feature portion may have an illuminance level higher than a predetermined illuminance level or comprises a predetermined shape, and is selected from among a plurality of feature portions in the input image.
- the determining of whether the input image includes a representative feature portion may include: extracting the plurality of feature portions from the input image; selecting a candidate feature portion having a predetermined feature from among the extracted feature portions; and determining that the input image includes the representative feature portion if the enlarged sampled image includes the candidate feature portion, and determining that the input image does not include the representative feature portion if the enlarged sampled image does not include the candidate feature portion.
- the matching of the enlarged sampled image with the sampled image may include performing scale invariant feature transform (SIFT) matching if the sampled image is enlarged at a magnification equal to or less than 2.5.
- SIFT scale invariant feature transform
- the matching of the enlarged sampled image with the sampled image may include performing template matching by resizing the sampled image by a magnification at which the sampled image is enlarged if the sampled image is enlarged at a magnification equal to or greater than 2.5.
- a method of image stabilization including: determining whether an input image comprises a representative feature portion; calculating optical flows of the input image during enlargement of the input image, if it is determined that the input image does not comprise the representative feature portion; obtaining optical axis error information by using optical flow information obtained from the calculated optical flows; and aligning an optical axis by using the obtained optical axis error information.
- the calculating of the optical flows may include obtaining the input image according to a predetermined number of frames during the enlargement of the input image.
- the obtaining of the optical axis error information may include forming an optical flow histogram based on at least one distance from a center of the input image and at least one direction at each of the at least one distance.
- the optical axis error information may be obtained only if directions of minimum and maximum values of the optical flows at each of the at least one distance are symmetrical to each other.
- the optical axis error information may be obtained based on a difference between an average value and a minimum value of the optical flows at each of the at least one distance.
- an image stabilization system including: a representative feature portion presence determining unit which determines whether an input image comprises a representative feature portion; a sampling unit which samples the representative feature portion to generate a sample image if it is determined that the input image comprises the representative feature portion; a matching unit which enlarges the sampled image, matches the enlarged sampled image with the sampled image, and obtains a central coordinate of the matched image; and an optical axis aligning unit which aligns an optical axis by calculating a difference between the central coordinate of the matched image and a central coordinate of the sampled image.
- the representative feature portion may have an illuminance level higher than a predetermined illuminance level or comprises a predetermined shape, and is selected from among a plurality of feature portions in the input image.
- the representative feature portion presence determining unit may extract the plurality of feature portions from the input image, select a candidate feature portion having a predetermined feature from among the extracted feature portions, determine that the input image includes the representative feature portion if the enlarged sampled image includes the candidate feature portion, and determine that the input image does not include the representative feature portion if the enlarged sampled image does not include the candidate feature portion.
- the matching unit may match the enlarged sampled image with the sampled image by scale invariant feature transform (SIFT) matching if the sampled image is enlarged at a magnification equal to or less than 2.5.
- SIFT scale invariant feature transform
- the matching unit may match the enlarged sampled image with the sampled image by template matching by resizing the sampled image by the magnification at which the sampled image is enlarged if the sampled image is enlarged at a magnification equal to or greater than 2.5.
- an image stabilization system including: a representative feature portion presence determining unit which determines whether an input image comprises a representative feature portion; an optical flow calculating unit which calculates optical flows of the input image during enlargement of the input image, if it is determined that the input image does not comprise the representative feature portion; an error information extracting unit which obtains optical axis error information by using optical flow information obtained from the calculated optical flows; and an optical axis aligning unit which aligns an optical axis by using the obtained optical axis error information.
- the optical flow calculating unit may calculate the optical flows by obtaining the input image according to a predetermined number of frames during the enlargement of the input image.
- the error information extracting unit may obtain the optical axis error information by forming an optical flow histogram based on at least one distance from a center of the input image and at least one direction at least of the at least one distance.
- the error information extracting unit may obtain the optical axis error information only if directions of minimum and maximum values of the optical flows at each of the at least one distance are symmetrical to each other.
- the error information extracting unit may obtain the optical axis error information based on a difference between an average value and a minimum value of the optical flows at each of the at least one distance.
- a zoom camera including: a representative feature portion presence determining unit which determines whether an input image comprises a representative feature portion; an optical axis error calculating unit which obtains optical axis error information by matching a sample image including the representative feature portion and an enlarged sample image if the representative feature portion presence determining unit determines that the input image comprises a representative feature portion, and obtaining the optical axis error information by calculating optical flow information between at least two images corresponding to the input image if the representative feature portion presence determining unit determines that the input image does not comprise the representative feature portion; and an optical axis aligning unit which compensates for an optical axis error by using the obtained optical axis error information.
- FIGS. 1A to 1C are images showing when an optical axis error occurs in an image captured by a zoom camera
- FIG. 2 is a block diagram of an image stabilization system according to an exemplary embodiment
- FIGS. 3A to 3D are views showing examples for detecting a representative feature portion according to an exemplary embodiment
- FIG. 4 is a view showing that a direction in which an optical axis error may occur is approximated to eight directions according to an exemplary embodiment
- FIGS. 5A to 5C are views showing an image obtained by sampling the image of FIGS. 1A to 1C , an image obtained by enlarging the sampled image, and an image obtained by matching the sampled image with an enlarged or resized image of the sampled image, respectively, according to an exemplary embodiment;
- FIG. 6 is a view showing size information of an optical flow according to distances from a center of an image when an optical axis is moved to the right upper side according to an exemplary embodiment
- FIG. 7 is a flowchart for describing an image stabilization system according to an exemplary embodiment
- FIG. 8 is a flowchart for describing a method of determining whether an image includes a representative feature portion, according to an exemplary embodiment
- FIG. 9 is a flowchart for describing a process of calculating an optical flow by an optical flow calculating unit, according to an exemplary embodiment.
- FIG. 10 is a flowchart for describing a process of extracting an optical axis error by using optical flow information by an error information extracting unit, according to an exemplary embodiment.
- FIG. 2 is a block diagram of an image stabilization system according to an exemplary embodiment.
- the image stabilization system includes a zoom camera 1 , an image preprocessor 10 , a representative feature portion presence determining unit 20 , a sampling unit 31 , a matching unit 32 , an optical flow calculating unit 33 , an error information extracting unit 34 , and an optical axis aligning unit 40 .
- the zoom camera 1 is installed in an area where image capture is required and provides an image obtained capturing the area.
- the zoom camera 1 is an apparatus capable of capturing an image, for example, a camera, a camcorder, or a closed-circuit television (CCTV).
- the zoom camera 1 may provide a function to enlarge an input image.
- the image preprocessor 10 converts an analog signal of image data input by the zoom camera 1 into a digital signal. Although the image preprocessor 10 is disposed outside of the zoom camera 1 in FIG. 2 , the image preprocessor 10 may be disposed inside the zoom camera 1 .
- the representative feature portion presence determining unit 20 determines whether the input image obtained from the zoom camera 1 has a feature portion.
- a representative feature portion of an image refers to a portion of the image which is a criterion used to determine an optical axis error in an input image.
- the representative feature portion refers to a portion of the image having a particularly high illuminance and a distinctive shape so that even comparing an enlarged image with the image before its enlargement during image processing, a user may clearly recognize that both images are the same.
- the input image may have one or more representative feature portions.
- FIGS. 3A to 3D are views showing examples for detecting a representative feature portion according to an exemplary embodiment.
- the image of FIG. 3A has a plurality of feature portions.
- the representative feature portion presence determining unit 20 may determine a portion where some of a plurality of feature portions overlap with one another or a strong feature portion to be a candidate feature portion.
- the candidate feature portion determined to be a representative feature portion by the representative feature portion presence determining unit 20 is marked with a black star.
- an enlarged image of an area Z 1 may not include a candidate feature portion.
- the representative feature portion presence determining unit 20 may redetermine the candidate feature portion in the area Z 1 .
- the representative feature portion presence determining unit 20 may determine the candidate feature portion to be a representative feature portion.
- the representative feature portion presence determining unit 20 may determine that the image does not include a representative feature portion. If the image does not include a representative feature portion, optical axis error information may be obtained by using optical flow information, as described later.
- the representative feature portion presence determining unit 20 may determine whether an input image includes a representative feature portion only in a specific direction. In the zoom camera 1 , since an optical axis error generally occurs only in one direction, the representative feature portion presence determining unit 20 may determine the presence of a feature portion only in a direction in which the optical axis error occurs to reduce an amount of operations.
- FIG. 4 is a view showing that a direction in which an optical axis error may occur is approximated to eight directions according to an exemplary embodiment.
- the representative feature portion presence determining unit 20 may determine the presence of a representative feature portion only in eight directions as shown in FIG. 4 so as to reduce an amount of operations compared to when the presence of the representative feature portion in all directions is detected.
- the sampling unit 31 samples a portion of an image including a feature portion.
- An area where the sampling is performed by the sampling unit 31 includes a feature portion and may have a size suitable for matching between images.
- the input image may include a plurality of sampled areas as well.
- the sampling unit 31 may obtain a central coordinate of the sampled area.
- the central coordinate obtained from the sampled area may be represented by (x_s, y_s).
- FIGS. 5A to 5C are views showing an image obtained by sampling the image of FIGS. 1A to 1C , an image obtained by enlarging the sampled image, and an image obtained by matching the sampled image with an enlarged or resized image of the sampled image, respectively, according to an exemplary embodiment.
- the portion marked with ‘+’ in the image of FIG. 1A that is, a central area and a peripheral area of the image, are sampled.
- the representative feature portion presence determining unit 20 determines that a light in the center of the image is a representative feature portion, a predetermined area including the light may be obtained as a sampled image as shown in FIG. 5A .
- the sampling unit 31 may resize the sampled image, as shown in FIG. 5B , to perform template matching to be described below.
- the matching unit 32 matches a sampled image with an enlarged image of the input image. If the input image is enlarged at a magnification equal to or less than 2.5, the matching unit 32 performs matching by scale invariant feature transform (SIFT) matching.
- SIFT scale invariant feature transform
- the SIFT matching is used to smoothly match images by extracting a feature point generated in an edge or a vertex of an object as a vector even though the image is changed due to, for example, a change in a size, rotation, or a change in light.
- the SIFT matching may match the enlarged input image with the sampled image regardless of a size and a direction of the image in view of characteristics of the SIFT matching.
- the matching unit 32 may enlarge the input image at a remaining magnification after matching if the input image is enlarged at a magnification equal to or greater than 2.5, and may perform a repetitive compensating method including matching and compensating for the sampled image if an optical axis is moved. Accordingly, the matching unit 32 may perform template matching by resizing the sampled image by a magnification at which the sampled portion is enlarged if the input image is enlarged at a magnification equal to or greater than 2.5.
- the matching unit 32 obtains a central coordinate of the matched area after the matching.
- the matching unit 32 may obtain a central coordinate of a matched area in the image of FIG. 5A , for example, that is, a central coordinate of a brightest area.
- the obtained central coordinate may be represented by (x_m, y_m).
- the optical axis aligning unit 40 may move the zoom camera 1 by (x_s-x_m) in a pan direction and by (y_s-y_m) in a tilt direction by using the obtained central coordinate.
- the representative feature portion presence determining unit 20 determines that an image does not include a representative feature portion and a plurality of feature points are scattered throughout the image, a general SIFT matching method or template matching method may not be used. In this case, the representative feature portion presence determining unit 20 extracts and compensates for an optical axis error of the zoom camera 1 by calculating an optical flow between images. According to an exemplary embodiment, the representative feature portion presence determining unit 20 may determine that an image does not include a representative feature portion if the image does not have any portion with an illuminance level higher than a predetermined level.
- the optical flow calculating unit 33 calculates an optical flow between images while the zoom camera 1 is enlarging the images.
- the optical flow calculating unit 33 may set an image before its enlargement as an image A_ 0 and may set an image after a predetermined period of time elapses (after N frames) as an image A_ 1 , where N is an integer greater than or equal to 1.
- N is an integer greater than or equal to 1.
- To calculate an optical flow of an image in every frame increases an amount of operations, and thus, process efficiency may be decreased. Accordingly, in the current embodiment, the amount of operations may be reduced without missing a feature portion by calculating an optical flow of an image at predetermined frames.
- the optical flow calculating unit 33 may store optical flow information at the time of enlargement using the image A_ 0 and the image A_ 1 as OF_ 1 . By using such a method, the optical flow calculating unit 33 may obtain image information A_ 0 , A_ 1 , A_ 2 , . . . , A_k at every (N+1)-th frame and obtains optical flow information OF_ 0 , OF_ 1 , OF_ 2 , . . . , OF_k ⁇ 1 between images, where k is an integers greater than or equal to 1.
- the error information extracting unit 34 obtains distances from centers of images of the optical flows by using the obtained optical flow information, and then, forms a two-dimensional (2D) histogram with respect to L distances and M directions, where L and M each are integers greater than or equal to 1.
- the error information extracting unit 34 extracts a minimum value and a maximum value of an optical flow with respect to each direction at each distance with reference to the formed 2D histogram.
- a size of an optical flow is proportional to a distance from the center of the image in view of characteristics of a camera curvature, reliable information may be extracted by obtaining the direction and the size of the optical flow for each of the distances, and thus, the error information extracting unit 34 obtains distances of optical flow feature portions from the center of the image.
- FIG. 6 is a view showing size information of an optical flow according to distances from a center of an image when an optical axis is moved to the right upper side according to an exemplary embodiment.
- FIG. 6 shows when an optical axis of the zoom camera 1 is moved to the upper-right side, in a direction (a). If the optical axis of the zoom camera 1 is not moved, an optical flow of an area C 1 spaced apart from a center C of an image at a distance d will have a radial form outside of a circle in an equal size.
- the direction (a) in an optical flow of an area C 1 spaced apart from the center C of the image at the distance d, the direction (a) has a size smaller than that of a direction (b).
- an optical flow in the direction (a) located on the area C 1 and an optical flow in the direction (b) have different sizes, unlike a case where the optical axis error does not occur.
- the optical flow in the direction (a) is smaller than that in the direction (b) because the center C of the image is moved in the direction (a) compared to the image before its enlargement.
- the size of the optical flow increases.
- the size of the optical flow increases in the order of the areas C 1 , C 2 , and C 3 because the area that is far away from the center C of the image moves further when enlarging the image by using the zoom camera 1 .
- the error information extracting unit 34 may form a histogram in M directions with respect to L distances by using the optical flow information obtained by the optical flow calculating unit 33 .
- the error information extracting unit 34 may set the L distances at an appropriate level within a range in which an amount of operations is not excessively increased.
- L may be three as in FIG. 6 .
- the M directions may be set to eight. If the entire angle area is divided into eight, as shown in FIG. 4 , approximation with respect to the angle is performed, and thus, an approximate value with respect to an adjacent direction may be considered to decrease an error.
- the error information extracting unit 34 extracts a minimum value and a maximum value of an optical flow with respect to each direction at each distance based on the formed histogram.
- the size of the optical flow is proportional to the distance from the center of the image in view of characteristics of an optical axis error of the zoom camera 1 , directions and sizes of the optical flow are different from one another, and thus, the error information extracting unit 34 extracts the minimum value and the maximum value.
- sizes of optical flows at an area in a same distance from the center C are different from each other, and the sizes of the optical flows are different from one another in the areas C 1 , C 2 , and C 3 spaced apart from the center C of the image at different distances.
- the size of the optical flow increases, and the optical flow in the direction (a) that is the same as the direction of the optical axis error is smaller than the optical flow in the direction (b). Accordingly, reliable error compensation may be performed by obtaining optical axis error data with respect to both the distance and direction.
- the error information extracting unit 34 determines whether directions of the minimum and maximum values are symmetrical to each other, and, if the directions of the minimum and maximum values are symmetrical to each other, obtains a difference between the minimum value and an average value of the optical flows at each distance. Based on the difference between the minimum value and the average value of the optical flows at each distance, the error information extracting unit extracts the error information by calculating a sum of the differences at the L distances and dividing the sum by L.
- the directions of the minimum and maximum values are symmetrical to each other.
- the size of the optical flow is small in the direction (a) in which the optical axis is moved and is large in the direction (b) opposite to the direction (a), the directions of the minimum and maximum values are symmetrical to each other. If the directions of the minimum and maximum values are not symmetrical to each other, it is determined that the optical axis is not moved to any one direction, which makes it difficult to extract optical axis error information by using a change in the optical flow.
- the error information extracting unit 34 obtains a difference between the minimum value and the average value of optical flows at each of the L distances, adds up the differences obtained at the L distances, and divides a sum of the differences by L to extract error information of an optical axis. That is, the error information extracting unit 34 may obtain the optical axis error information by using the calculated average value. Referring back to FIG. 6 , the optical axis error information in the distance C 1 may be obtained by calculating a difference between the minimum value and the average value of the optical flows at the distance C 1 .
- the optical axis aligning unit 40 compensates for an optical axis error by using the optical axis error information obtained by the matching unit 32 and the error information extracting unit 34 .
- the compensation for the optical axis error may be performed through image processing by converting a degree to which an optical axis is moved into a coordinate instead of using a physical method.
- FIG. 7 is a flowchart for describing an image stabilization system according to an exemplary embodiment.
- the image stabilization system obtains an input image having a specific zoom value by using the zoom camera 1 (operation S 1 ).
- the representative feature portion presence determining unit 20 determines whether the obtained input image includes a representative feature portion (operation S 2 ).
- the representative feature portion may refer to a portion of the input image set as a representative value to compensate for the optical axis error from among a plurality of distinctive feature portions during image processing.
- the representative feature portion presence determining unit 20 determines that the input image includes the representative feature portion
- the representative feature portion of the input image is sampled to generate a sampled image, and a central coordinate of a sampled area is obtained and set as (x_s, y_s) (operation F 1 ).
- the input image is enlarged by using the zoom camera 1 , and image information of an enlarged area of the input image is obtained (operation F 2 ).
- the sampled image and enlarged input image are matched with each other by SIFT matching (operation F 4 ).
- the sampled image may be resized by the magnification at which the input image is enlarged, and then the sampled image and enlarged input image are matched with each other by template matching (operation F 5 ).
- the optical axis aligning unit 40 aligns the moved optical axis by moving the central coordinate by (x_s-x_m) in a pan direction and by (y_s-y_m) in a tilt direction to compensate for the optical axis error.
- the optical flow calculating unit 33 obtains an image right before enlarging the input image (operation O 1 ).
- the optical flow calculating unit 33 enlarges an image by using the zoom camera 1 and calculates an optical flow of the image during the enlargement of the image (operation O 2 ).
- the error information extracting unit 34 extracts optical axis error information by using optical flow information (operation O 3 ).
- the error information extracting unit 34 may obtain the optical axis error information based on the optical flow information in a movement direction of the optical flow and an opposite direction thereto by using a fact that an optical axis is moved only in one direction.
- the optical axis aligning unit 40 compensates for an optical error by moving pan and tilt values by a size of the optical axis error information in an opposite direction to a direction of the optical axis error information (operation O 4 ).
- FIG. 8 is a flowchart for describing a method of determining whether an image includes a representative feature portion, according to an exemplary embodiment.
- the representative feature portion presence determining unit 20 extracts all feature portions from an image before its enlargement (operation S 21 ).
- a feature portion that may be a representative feature portion in the image is set as a candidate feature portion (operation S 22 ), and the image is enlarged (operation S 23 ).
- the enlarged image includes a candidate feature portion, it is determined whether the image needs to be additionally enlarged (operation S 26 ). If the image needs to be additionally enlarged, the method returns to operation S 23 , and the operation is repeated.
- the representative feature portion presence determining unit 20 sets the set candidate feature portion as a representative feature portion (operation S 27 ).
- the representative feature portion presence determining unit 20 may determine that the input image does not include a representative feature portion.
- FIG. 9 is a flowchart for describing a process of calculating an optical flow by the optical flow calculating unit 33 , according to an exemplary embodiment.
- the optical flow calculating unit 33 obtains an image right before its enlargement and stores the image as an image A_ 0 (operation O 21 ).
- the optical flow calculating unit 33 calculates optical flows between the image A_ 0 and an image A_ 1 after N frames, and stores the optical flows as OF_ 1 (operation O 22 ).
- the optical flow calculating unit 33 calculates optical flows between the image A_ 1 and of an image A_ 2 after N frames from the frame of the image A_ 1 , and stores the optical flows as OF_ 2 (operation O 23 ).
- the optical flow calculating unit 33 calculates optical flows of an image A_k ⁇ 1 and an image A_k at an interval of N frames, and stores the optical flows as OF_k ⁇ 1 by using the above-described method (operation O 24 ). For the efficiency of operation, the optical flow calculating unit 33 calculates an optical frame in every (N+1)-th frame instead of calculating an optical flow of an image in every frame.
- FIG. 10 is a flowchart for describing a process of extracting an optical axis error by using optical flow information by the error information extracting unit 34 , according to an exemplary embodiment.
- the error information extracting unit 34 calculates distances of stored optical flow feature portions from a center of an image (operation O 31 ).
- the error information extracting unit 34 forms an optical flow histogram in M directions with respect to the L distances from the center of the image (operation O 32 ). As described above, referring to FIGS. 4 and 6 , the error information extracting unit 34 may form the optical flow histogram in eight directions with respect to three distances from the center of the image.
- the error information extracting unit 34 extracts a maximum value and a minimum value in every direction with respect to the L distances (operation O 33 ). As described above, when an optical axis is moved in any one direction, an optical flow in the direction in which the optical axis is moved has a minimum value and an optical flow in an opposite direction to the direction in which the optical axis is moved has a maximum value.
- the error information extracting unit 34 may calculate optical axis error information by using a difference between the maximum value and the minimum value.
- the error information extracting unit 34 determines whether directions of the minimum and maximum values are symmetrical to each other at each of the L distances (operation O 34 ). If the optical axis is moved in any one direction, the directions of the minimum and maximum values are symmetrical to each other.
- the error information extracting unit 34 extracts an average value of optical flows at each of the L distances and stores the average values as (Avg_ 1 , . . . , Avg_L) (operation O 35 ).
- the error information extracting unit 34 may not use feature portion information of the corresponding distances (operation O 36 ).
- the error information extracting unit 34 may extract the optical axis error information by obtaining a difference between the minimum value and the average value of optical flows at each of the L distances, adding up the differences obtained at the L distances, and dividing a sum of the differences by L.
- the optical axis error information may be obtained by an equation, ⁇ (Avg_a ⁇ Min_a)/L, where a is 1 to L. (operation O 37 ).
- an optical axis error system may effectively compensate for an optical axis error through image processing.
- the optical axis error may be compensated through image processing without physically changing setting of a zoom camera.
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KR101323609B1 (en) * | 2012-08-21 | 2013-11-01 | 주식회사 엠씨넥스 | Apparatus for aligning optical axis of a camera module |
KR101932547B1 (en) * | 2014-10-23 | 2018-12-27 | 한화테크윈 주식회사 | Camera system and Method of image registration thereof |
KR102352681B1 (en) | 2015-07-27 | 2022-01-18 | 삼성전자주식회사 | Method and electronic apparatus for stabilizing video |
KR102516175B1 (en) | 2017-12-21 | 2023-03-30 | 한화비전 주식회사 | Method and apparatus for correcting optical axis of zoom lens, and computer program for executing the method |
KR20210118622A (en) | 2020-03-23 | 2021-10-01 | 삼성전자주식회사 | Method for Stabilization at high magnification and Electronic Device thereof |
KR102171740B1 (en) * | 2020-07-28 | 2020-10-29 | 주식회사 원우이엔지 | Video surveillance device with AF zoom lens module capable of optical axis compensation |
CN113792708B (en) * | 2021-11-10 | 2022-03-18 | 湖南高至科技有限公司 | ARM-based remote target clear imaging system and method |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020136459A1 (en) * | 2001-02-01 | 2002-09-26 | Kazuyuki Imagawa | Image processing method and apparatus |
US6720997B1 (en) * | 1997-12-26 | 2004-04-13 | Minolta Co., Ltd. | Image generating apparatus |
KR100541618B1 (en) | 2003-12-29 | 2006-01-10 | 전자부품연구원 | Apparatus and method for controlling a monitoring camera |
US20060133785A1 (en) | 2004-12-21 | 2006-06-22 | Byoung-Chul Ko | Apparatus and method for distinguishing between camera movement and object movement and extracting object in a video surveillance system |
US20080310730A1 (en) * | 2007-06-06 | 2008-12-18 | Makoto Hayasaki | Image processing apparatus, image forming apparatus, image processing system, and image processing method |
US20090225174A1 (en) * | 2008-03-04 | 2009-09-10 | Sony Corporation | Image processing apparatus, image processing method, hand shake blur area estimation device, hand shake blur area estimation method, and program |
US20100229452A1 (en) | 2009-03-12 | 2010-09-16 | Samsung Techwin Co., Ltd. | Firearm system having camera unit with adjustable optical axis |
US20110169977A1 (en) * | 2010-01-12 | 2011-07-14 | Nec Casio Mobile Communications, Ltd. | Image quality evaluation device, terminal device, image quality evaluation system, image quality evaluation method and computer-readable recording medium for storing programs |
JP4767052B2 (en) | 2006-03-22 | 2011-09-07 | ダイハツ工業株式会社 | Optical axis deviation detector |
KR101076487B1 (en) | 2009-06-29 | 2011-10-24 | 중앙대학교 산학협력단 | Apparatus and method for automatic area enlargement control in ptz camera using sift |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP4112819B2 (en) | 2000-05-11 | 2008-07-02 | 株式会社東芝 | Object area information generation apparatus and object area information description program |
JP4196256B2 (en) | 2002-06-07 | 2008-12-17 | ソニー株式会社 | Object contour extraction device |
KR100588170B1 (en) * | 2003-11-20 | 2006-06-08 | 엘지전자 주식회사 | Method for setting a privacy masking block |
JP2006113738A (en) | 2004-10-13 | 2006-04-27 | Matsushita Electric Ind Co Ltd | Device and method for detecting object |
JP3941822B2 (en) | 2005-07-22 | 2007-07-04 | 横河電機株式会社 | Displacement measuring device |
JP2008269396A (en) * | 2007-04-23 | 2008-11-06 | Sony Corp | Image processor, image processing method, and program |
CN101334267B (en) * | 2008-07-25 | 2010-11-24 | 西安交通大学 | Digital image feeler vector coordinate transform calibration and error correction method and its device |
KR101341632B1 (en) * | 2008-11-05 | 2013-12-16 | 삼성테크윈 주식회사 | Optical axis error compensation system of the zoom camera, the method of the same |
KR20100082147A (en) * | 2009-01-08 | 2010-07-16 | 삼성전자주식회사 | Method for enlarging and changing captured image, and phographed apparatus using the same |
JP4752918B2 (en) * | 2009-01-16 | 2011-08-17 | カシオ計算機株式会社 | Image processing apparatus, image collation method, and program |
-
2011
- 2011-12-29 KR KR1020110146112A patent/KR101324250B1/en active IP Right Grant
-
2012
- 2012-12-28 CN CN201210583864.1A patent/CN103188442B/en active Active
- 2012-12-28 US US13/729,302 patent/US9031355B2/en active Active
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6720997B1 (en) * | 1997-12-26 | 2004-04-13 | Minolta Co., Ltd. | Image generating apparatus |
US20020136459A1 (en) * | 2001-02-01 | 2002-09-26 | Kazuyuki Imagawa | Image processing method and apparatus |
KR100541618B1 (en) | 2003-12-29 | 2006-01-10 | 전자부품연구원 | Apparatus and method for controlling a monitoring camera |
US20060133785A1 (en) | 2004-12-21 | 2006-06-22 | Byoung-Chul Ko | Apparatus and method for distinguishing between camera movement and object movement and extracting object in a video surveillance system |
JP2006180479A (en) | 2004-12-21 | 2006-07-06 | Samsung Electronics Co Ltd | Apparatus and method for distinguishing between camera movement and object movement and extracting object in video monitoring system |
JP4767052B2 (en) | 2006-03-22 | 2011-09-07 | ダイハツ工業株式会社 | Optical axis deviation detector |
US20080310730A1 (en) * | 2007-06-06 | 2008-12-18 | Makoto Hayasaki | Image processing apparatus, image forming apparatus, image processing system, and image processing method |
US20090225174A1 (en) * | 2008-03-04 | 2009-09-10 | Sony Corporation | Image processing apparatus, image processing method, hand shake blur area estimation device, hand shake blur area estimation method, and program |
US20100229452A1 (en) | 2009-03-12 | 2010-09-16 | Samsung Techwin Co., Ltd. | Firearm system having camera unit with adjustable optical axis |
KR20100102959A (en) | 2009-03-12 | 2010-09-27 | 삼성테크윈 주식회사 | Firearm system having camera unit with adjustable optical axis |
KR101076487B1 (en) | 2009-06-29 | 2011-10-24 | 중앙대학교 산학협력단 | Apparatus and method for automatic area enlargement control in ptz camera using sift |
US20110169977A1 (en) * | 2010-01-12 | 2011-07-14 | Nec Casio Mobile Communications, Ltd. | Image quality evaluation device, terminal device, image quality evaluation system, image quality evaluation method and computer-readable recording medium for storing programs |
Non-Patent Citations (3)
Title |
---|
Amanatiadis et al. ("An integrated architecture for adaptive image stabilization in zooming operation," IEEE Trans. Consumer Electronics, vol. 54, No. 2, 2008, pp. 600-608). * |
Kim et al. ("Automatic radial distortion correction in zoom lens video camera," J. Electronic Imaging, 19(4), 2010). * |
Yoneyama et al. ("Lens distortion correction for digital image correlation by measuring rigid body displacement," Opt. Eng. 45(2), 2006). * |
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